Dr Fiona Fidler
||Natural Philosophy Building|
|Phone||+61 3 8344 3336|
|Fax||+61 3 9348 1620|
I am a psychologist working in Environmental Science. I’m interested in how scientists and experts make decisions. My undergraduate degree was in Behavioural Science, my PhD was in History and Philosophy of Science and I spent 4 years as an ARC postdoctoral fellow in Psychology. I am currently part of the Australian Centre of Excellence for Risk Analysis (ACERA). My two ongoing research projects are:
My projects in statistical cognition involve identifying typical misconceptions about statistical concepts and developing graphical displays, language and teaching resources for improved statistical communication. These projects are strongly connected to the statistical reform of psychology and other disciplines. Statistical reform involves a move away from over-reliance on statistical significance testing and dichotomous decisions made on the basis of p values to effect size estimation, confidence intervals, Bayesian techniques and other methods.
Overconfidence in quantity judgments is a common phenomenon. For example, when asked to guess a 90% interval for some value, people will typically return bounds that correspond with 50% intervals. In other words, they severely underestimate their own uncertainty. In experts, overconfidence may be often more pronounced. My research looks for ways of eliciting judgments from experts that have less systematic narrowing, and so more accurately characterise uncertainty.
Member, Association of Psychological Science (APS)
Member, American Psychological Association (APA)
Member, Society for Judgment and Decision Making (JDM)
I am an associate editor of Frontiers in Quantitative Psychology and Measurement
Fidler, F. (under contract). From Statistical Significance to Effect Estimation: Statistical Reform in Psychology, Medicine and Ecology. Routledge/Taylor and Francis.
Wintle, B., Fidler, F., Vesk, P. & Moore, J. (in press). Improving visual estimation through active feedback. Methods in Ecology and Evolution.
Hicks, J.S., Burgman, M.A., Marewski, J.N., Fidler, F. & Gigerenzer, G. (2012). Decision making in a human population living sustainably. Conservation Biology, 26, 760-76.
Abbot, J.D., Cumming, G., Fidler, F. & Lindell, A.K. (2012). The perception of positive and negative facial expressions in unilateral brain-damaged patients: A meta-analysis. Laterality,
Vaux, D.L., Fidler, F. & Cumming, G. (2012). Replicates and repeats—what is the difference and is it significant? A brief discussion of statistics and experimental design. EMBO reports, 13, 291-6.
Martin, T., Burgman, M., Fidler, F., Kuhnert, P.M., Low-Choy, S., McBride, M. & Mengerson, K. (2012). Eliciting expert knowledge in conservation science. Conservation Biology, 6, 29-38.
McBride, M., Fidler, F. & Burgman, M. (2012). Evaluating the accuracy and calibration of expert predictions under uncertainty: Predicting the outcomes of ecological research. Diversity and Distributions, 18, 782-794.
Burgman, M.A., McBride, M., Ashton, R., Speirs-Bridge, A., Flander, L., Wintle, B., Fidler, F., Rumpff, L. & Twardy, C. (2011). Expert status and performance. PLOS-one, 6, e22998.
Cumming, G., Fidler, F., Kalinowski, P., & Lai, J. (2011). The statistical recommendations of the American Psychological Association Publication Manual: Effect sizes, confidence intervals, and meta-analysis. Australian Journal of Psychology. doi:10.1111/j.1742-9536.2011.00037.x
Lai, J., Fidler, F. & Cumming, G. (2011). Subjective p intervals: Researchers underestimate the variability of p values over replication. Methodology, 8, 51-62.
Schwab, A., Abrahamson, E., Starbuck, W.H., & Fidler, F. (2011). Perspective—Researchers Should Make Thoughtful Assessments Instead of Null-Hypothesis Significance Tests. Organization Science, 21. Published online before print August 20, 2010, DOI:10.1287/orsc.1100.0557.
Kalinowski, P., Lai, J., Fidler, F. & Cumming, G. (2010). Qualitative Research: An essential part of Statistical Cognition. Statistics Education Research Journal (SERJ), 9, 22-34. http://www.stat.auckland.ac.nz/serj.
Coulson, M., Healey, M., Fidler, F. & Cumming, G. (2010). Confidence Intervals permit, but don’t guarantee, better inference than statistical significance testing. Frontiers in Quantitative Psychology and Measurement,1. doi: 10.3389/fpsyg.2010.00026.
Kalinowski, P. & Fidler, F. (2010). Interpreting ‘significance’: The difference between statistical and practical importance. Newborn and Infant Nursing Review, 10, 50-54.
Fidler, F. & Loftus, G. (2009). Why figures with error bars should replace p values: Some conceptual arguments and empirical demonstrations. Zeitschrift fuer Psychologie / Journal of Psychology, 217, 27-37.
Cumming, G. & Fidler, F. (2009). Confidence Intervals: Better answers to better questions. Zeitschrift fuer Psychologie / Journal of Psychology, 217, 15-26.
Speirs-Bridge, A., Fidler, F., McBride, M., Flander, L., Cumming, G. & Burgman, M. (2009). Reducing overconfidence in the interval judgements of experts. Risk Analysis, 30, 512 – 523.
Beyth-Marom, R., Fidler, F. & Cumming, G. (2008). Statistical Cognition: Towards evidence-based practice in statistics and statistics education. Statistics Education Research Journal, 7, 20-39.
Kalinowski, P., Fidler, F. & Cumming, G. (2008). Overcoming the inverse probability fallacy: A comparison of two teaching interventions. Methodology, 4, 152-158.
Faulkner, C., Fidler, F. & Cumming, G. (2008). The value of RCT evidence depends on the quality of statistical analysis. Behaviour Research and Therapy, 46, 270-281.
Walshe,T., Wintle, B., Fidler, F. & Burgman, M. (2007). Use of confidence intervals to demonstrate performance against forest management standards. Forest Ecology and Management, 247, 237-245.
Wintle, B., Burgman, M. & Fidler, F. (2007). How fast should nanotechnology advance? Nature Nanotechnology, 2, 327.
Cumming, G., Fidler, F., & Vaux, D. L. (2007). Error bars in experimental biology. Journal of Cell Biology, 177, 7-11. [Feature article] [Reprinted in Journal of Experimental Medicine, April 2007, 204, i11.]
Fidler, F. & Cumming, G. (2007). Lessons learned from statistical reform efforts in other disciplines. Special Issue: Statistical reform in school psychology (Thomas J. Kehle and Melissa A. Bray, Eds.) Psychology in the Schools, 44, 441-449.
Cumming, G., Fidler, F., Leonard, M., Kalinowski, P., Christiansen, A., Kleinig, A., Lo, J., McMenamin, N. & Wilson, S. (2007). Statistical reform in psychology: Is anything changing? Psychological Science, 18, 230-232.
Fidler, F., Burgman, M., Cumming, G. Buttrose, R. & Thomason., N. (2006). Impact of criticism of null hypothesis significance testing on statistical reporting practices in conservation biology. Conservation Biology, 20, 1539-1544.
Belia, S., Fidler, F., Williams, J. & Cumming, G. (2005). Researchers misunderstand confidence intervals and standard error bars. Psychological Methods, 10, 389-396.
Fidler, F., Thomason, N., Cumming, G., Finch, S. & Leeman, J. (2005). Still much to learn about confidence intervals. Reply to Rouder and Morey. Psychological Science,16, 494-495.
Fidler, F., Cumming, G., Thomason, N., Pannuzzo, D., Smith, J., Fyffe, P., Edmonds, H., Harrington, C. & Schmitt, R. (2005). Toward improved statistical reporting in the Journal of Consulting and Clinical Psychology. Journal of Consulting and Clinical Psychology, 73, 136-143.
Fidler, F., Cumming, G., Burgman, M. & Thomason, N. (2004). Statistical reform in medicine, psychology and ecology. Journal of Socio Economics, 33, 615-630.
Fidler, F., Thomason, N., Cumming, G., Finch, S. & Leeman, J. (2004). Editors can lead researchers to confidence intervals but they can't make them think: Statistical reform lessons from Medicine. Psychological Science, 15, 119-126.
Cumming, G., Williams, J., & Fidler, F. (2004). Replication, and researchers’ understanding of confidence intervals and standard error bars. Understanding Statistics, 3, 299-311.
Fidler, F. (2002). The 5th edition of the APA Publication Manual: Why its statistics recommendations are so controversial. Educational and Psychological Measurement, 62, 749-770.Fidler, F. & Thompson, B. (2001). Computing Correct Confidence Intervals for ANOVA fixed and random effect sizes. Educational and Psychological Measurement, 61, 575-604.
Geoff Cumming's webpage has pdfs of many of our joint papers: http://www.latrobe.edu.au/psy/cumming/current_res.html
Fidler, F. (2011). Ethics and Statistical Reform: Lessons from Medicine.In A. Panter & S. Sterba (Eds.) The ethics of quantitative methodology: A handbook for researchers. Taylor and Francis (Multivariate Application Book Series). Ch 17, pp. 445-462.
Fidler, F. & Cumming, G. (2011).From Hypothesis Testing to Estimation. In A. Panter & S. Sterba (Eds.) The ethics of quantitative methodology: A handbook for researchers. Taylor and Francis (Multivariate Application Book Series). Ch 11, pp. 293-312. Ch 4, pp. 71-88.
Fidler, F. (2010). Statistical Significance, Result Worthiness and Evidence: What lessons are there for giftedness education in other disciplines? In B. Thompson & R. Subotnik (Eds.). Research methodologies for conducting research on giftedness. Washington, USA: American Psychological Association. Ch 4, pp. 71-88.
Cumming, G., & Fidler, F. (2010). The new stats: Effect sizes and confidence intervals. In G. R. Hancock & R. O. Mueller (Eds.) The reviewers’ guide to quantitative methods in the social sciences. Erlbaum. Ch 7, pp. 79-92.
Fidler, F., & Cumming, G. (2008). The new stats: Attitudes for the twenty-first century. (Ch 1) In J.W. Osborne (Ed.). Best practice in quantitative methods (pp. 1-12). Sage. Ch 1, pp. 1-12.
Fidler, F., Faulkner, S., & Cumming, G. (2008). Analyzing and presenting outcomes: Focus on effect size estimates and confidence intervals. In A. M. Nezu & C. M. Nezu (Eds.) Evidence-based outcome research: A practical guide to conducting randomized controlled trials for psychosocial interventions. New York: OUP. Ch 15, pp. 315-334.
DiStefano, J., Fidler, F. & Cumming, G. (2005). Effect size estimates and confidence intervals: An alternative focus for the presentation and interpretation of ecological data. (Ch 3, pp. 71-102). In A.R. Burk (Ed.) New Trends in Ecology Research. Hauppauge NY: Nova Science Publishers.
Fidler, F. (2010). The American Psychological Association Publication Manual Sixth Edition: Implications for teaching statistics. Data and context in statistics education: Towards an evidence-based society. Proceedings of ICOTS-8, Eighth International Conference on Teaching Statistics. Ljubljana, Slovenia.
Fidler, F. (2006). Should Psychology abandon
p values and teach confidence intervals instead? Evidence-based
reforms in statistics education. Working co-operatively
in statistics education. Proceedings of ICOTS-7, Seventh
International Conference on Teaching Statistics. Salvador,
Cumming, G. & Fidler, F. (2005). Interval estimates for statistics communication: Problems and possible solutions. Proceedings of Statistics Education and the Communication of Statistics, International Association for Statistics Education. Sydney, Australia.
Fidler, F. (2005).Confidence Intervals in practice. Proceedings of the 55th International Statistics Institute Session. Sydney, Australia.
Fidler, F. & Cumming, G. (2005). Teaching confidence intervals: Problems and potential solutions. Proceedings of the 55th International Statistics Institute Session. Sydney, Australia.
Cumming, G., Fidler, F. and Thomason, N. (2002). The statistical re-education of psychology. In B. Phillips (Ed.) Developing a statistically literate society. Proceedings of ICOTS-6, Sixth International Conference on Teaching Statistics, 1-6. Voorburg, The Netherlands.
Rachael Hamilton-Keene (2009). The ‘no overlap’ misconception of confidence intervals in medicine. School of Psychological Science, La Trobe University.
Debbie Hansen (2008). Reviewing clinical psychology: Meta-analysis
versus the narrative review. School of Psychological Science, La
Simon Carter (2007). Understanding confidence intervals: Interval
cognition and evaluation. School of Psychological Science, La Trobe
Andrew Speirs-Bridge (2007). The influence of elicitation format,
cognitive style, and forecast period on the rates-of-disease predictions
of infectious disease experts. School of Psychological Science,
La Trobe University.
Pawel Kalinowski (2006). Overcoming the inverse probability fallacy: A comparison of two teaching interventions. School of Psychological Science, La Trobe University.
Andrew Speirs-Bridge (2011). Professional training and expertise in Cognitive Behavioural Therapy. School of Psychological Science, La Trobe University.
Debbie Hansen (expected completion early 2013). Evidence-based Meta-Analysis. School of Psychological Science, La Trobe University.
Pawel Kalinowski (expected completion early 2013). The cognition of confidence intervals. (Supervising with Prof Geoff Cumming). School of Psychological Science, La Trobe University.
Jerry Lai (expected completion 2013). Statistical cognition of p values and confidence intervals: Implications for statistical reform in psychology. (Supervising with Prof Geoff Cumming). School of Psychological Science, La Trobe University.
Marissa McBride: http://www.botany.unimelb.edu.au/envisci/about/students/index.html
La Trobe Excellence in Research Award, 2009. Early Career Research Award in the Faculty of Science, Technology and Engineering. (1 only).
ARC Discovery Grant and Australian Post-doctoral Fellowship. 2007-2010. [ARC DP0770535]
Cumming, G. & Fidler, F. ‘Evidence based improvement of statistical inference practices in psychology and other disciplines.
Australian Centre of Excellence for Risk Analysis Research Grant. 2008. [ACERA 0805]
Thomason, N., Barnard, K., Carey, J. & Fidler, F. ‘Plain English for risk communication’
La Trobe University Grant. 2006. [based on near-miss ARC DP0664444] Cumming, G. & Fidler, F. ‘Improving statistical inference practices in psychology and other disciplines’
Australian Centre of Excellence for Risk Analysis Research Grant. June 2006-Nov 2009. [ACERA 0611] ‘Eliciting Expert Opinion’. (I was a named postdoc on this grant to M.Burgman).
Date Created: 13 December 2006